{"total":63,"rows":[{"id":"2503.05236","title":"Unified Reward Model for Multimodal Understanding and Generation","created":"2025-03-07","cited_by_count":199,"area":"alignment"},{"id":"2402.11411","title":"Aligning Modalities in Vision Large Language Models via Preference Fine-tuning","created":"2024-02-18","cited_by_count":198,"area":"alignment"},{"id":"2401.12187","title":"WARM: On the Benefits of Weight Averaged Reward Models","created":"2024-01-22","cited_by_count":147,"area":"alignment"},{"id":"2405.17220","title":"RLAIF-V: Open-Source AI Feedback Leads to Super GPT-4V Trustworthiness","created":"2024-05-27","cited_by_count":131,"area":"alignment"},{"id":"2402.02416","title":"Aligner: Efficient Alignment by Learning to Correct","created":"2024-02-04","cited_by_count":98,"area":"alignment"},{"id":"2403.05612","title":"Unfamiliar Finetuning Examples Control How Language Models Hallucinate","created":"2024-03-08","cited_by_count":87,"area":"alignment"},{"id":"2411.17451","title":"VL-RewardBench: A Challenging Benchmark for Vision-Language Generative Reward Models","created":"2024-11-26","cited_by_count":86,"area":"alignment"},{"id":"2402.09267","title":"Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-Evaluation","created":"2024-02-14","cited_by_count":80,"area":"alignment"},{"id":"2310.05910","title":"SALMON: Self-Alignment with Instructable Reward Models","created":"2023-10-09","cited_by_count":55,"area":"alignment"},{"id":"2405.19107","title":"Offline Regularised Reinforcement Learning for Large Language Models Alignment","created":"2024-05-29","cited_by_count":48,"area":"alignment"},{"id":"2503.20823","title":"Playing the Fool: Jailbreaking LLMs and Multimodal LLMs with Out-of-Distribution Strategy","created":"2025-03-26","cited_by_count":44,"area":"alignment"},{"id":"2412.15838","title":"Align Anything: Training All-Modality Models to Follow Instructions with Language Feedback","created":"2024-12-20","cited_by_count":39,"area":"alignment"},{"id":"2409.17407","title":"Post-hoc Reward Calibration: A Case Study on Length Bias","created":"2024-09-25","cited_by_count":29,"area":"alignment"},{"id":"2502.04370","title":"DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization","created":"2025-02-05","cited_by_count":27,"area":"alignment"},{"id":"2401.11458","title":"Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback","created":"2024-01-21","cited_by_count":25,"area":"alignment"},{"id":"2406.11191","title":"A Survey on Human Preference Learning for Large Language Models","created":"2024-06-17","cited_by_count":24,"area":"alignment"},{"id":"2409.11564","title":"Preference Tuning with Human Feedback on Language, Speech, and Vision Tasks: A Survey","created":"2024-09-17","cited_by_count":23,"area":"alignment"},{"id":"2410.18640","title":"Weak-to-Strong Preference Optimization: Stealing Reward from Weak Aligned Model","created":"2024-10-24","cited_by_count":22,"area":"alignment"},{"id":"2506.02095","title":"Cycle Consistency as Reward: Learning Image-Text Alignment without Human Preferences","created":"2025-06-02","cited_by_count":22,"area":"alignment"},{"id":"2503.18991","title":"Inverse Reinforcement Learning with Dynamic Reward Scaling for LLM Alignment","created":"2025-03-23","cited_by_count":20,"area":"alignment"},{"id":"2410.14148","title":"Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment","created":"2024-10-18","cited_by_count":19,"area":"alignment"},{"id":"2505.22338","title":"Text2Grad: Reinforcement Learning from Natural Language Feedback","created":"2025-05-28","cited_by_count":18,"area":"alignment"},{"id":"2505.02666","title":"A Survey on Progress in LLM Alignment from the Perspective of Reward Design","created":"2025-05-05","cited_by_count":15,"area":"alignment"},{"id":"2402.01920","title":"Preference Poisoning Attacks on Reward Model Learning","created":"2024-02-02","cited_by_count":14,"area":"alignment"},{"id":"2508.02374","title":"Uni-Layout: Integrating Human Feedback in Unified Layout Generation and Evaluation","created":"2025-08-04","cited_by_count":14,"area":"alignment"},{"id":"2403.06754","title":"ALaRM: Align Language Models via Hierarchical Rewards Modeling","created":"2024-03-11","cited_by_count":11,"area":"alignment"},{"id":"2411.11937","title":"Value Imprint: A Technique for Auditing the Human Values Embedded in RLHF Datasets","created":"2024-11-18","cited_by_count":11,"area":"alignment"},{"id":"2510.23451","title":"Omni-Reward: Towards Generalist Omni-Modal Reward Modeling with Free-Form Preferences","created":"2025-10-27","cited_by_count":11,"area":"alignment"},{"id":"2506.04721","title":"SPARTA ALIGNMENT: Collectively Aligning Multiple Language Models through Combat","created":"2025-06-05","cited_by_count":9,"area":"alignment"},{"id":"2506.12323","title":"Doctor Approved: Generating Medically Accurate Skin Disease Images through AI-Expert Feedback","created":"2025-06-14","cited_by_count":9,"area":"alignment"},{"id":"2509.00723","title":"OmniDPO: A Preference Optimization Framework to Address Omni-Modal Hallucination","created":"2025-08-31","cited_by_count":9,"area":"alignment"},{"id":"2504.14096","title":"VideoPASTA: 7K Preference Pairs That Matter for Video-LLM Alignment","created":"2025-04-18","cited_by_count":8,"area":"alignment"},{"id":"2505.18600","title":"Chain-of-Zoom: Extreme Super-Resolution via Scale Autoregression and Preference Alignment","created":"2025-05-24","cited_by_count":8,"area":"alignment"},{"id":"2412.00624","title":"VideoSAVi: Self-Aligned Video Language Models without Human Supervision","created":"2024-12-01","cited_by_count":7,"area":"alignment"},{"id":"2503.02989","title":"Effectively Steer LLM To Follow Preference via Building Confident Directions","created":"2025-03-04","cited_by_count":7,"area":"alignment"},{"id":"2403.14683","title":"A Moral Imperative: The Need for Continual Superalignment of Large Language Models","created":"2024-03-13","cited_by_count":5,"area":"alignment"},{"id":"2604.13029","title":"Visual Preference Optimization with Rubric Rewards","created":"2026-04-14","cited_by_count":5,"area":"alignment"},{"id":"2411.08923","title":"Aligning Visual Contrastive learning models via Preference Optimization","created":"2024-11-12","cited_by_count":4,"area":"alignment"},{"id":"2505.23950","title":"InterMT: Multi-Turn Interleaved Preference Alignment with Human Feedback","created":"2025-05-29","cited_by_count":4,"area":"alignment"},{"id":"2507.04340","title":"Interactive Groupwise Comparison for Reinforcement Learning from Human Feedback","created":"2025-07-06","cited_by_count":4,"area":"alignment"},{"id":"2410.07025","title":"CheXalign: Preference fine-tuning in chest X-ray interpretation models without human feedback","created":"2024-10-09","cited_by_count":3,"area":"alignment"},{"id":"2508.16921","title":"Being Kind Isn't Always Being Safe: Diagnosing Affective Hallucination in LLMs","created":"2025-08-23","cited_by_count":3,"area":"alignment"},{"id":"2601.04033","title":"Thinking with Frames: Generative Video Distortion Evaluation via Frame Reward Model","created":"2026-01-07","cited_by_count":3,"area":"alignment"},{"id":"2603.17044","title":"Do Understanding and Generation Fight? A Diagnostic Study of DPO for Unified Multimodal Models","created":"2026-03-17","cited_by_count":3,"area":"alignment"},{"id":"2605.20278","title":"ClaimDiff-RL: Fine-Grained Caption Reinforcement Learning through Visual Claim Comparison","created":"2026-05-19","cited_by_count":3,"area":"alignment"},{"id":"2410.18127","title":"Holistic Utility Preference Learning for Listwise Alignment","created":"2024-10-17","cited_by_count":2,"area":"alignment"},{"id":"2502.11681","title":"RIDE: Enhancing Large Language Model Alignment through Restyled In-Context Learning Demonstration Exemplars","created":"2025-02-17","cited_by_count":2,"area":"alignment"},{"id":"2503.03122","title":"The Devil Is in the Details: Tackling Unimodal Spurious Correlations for Generalizable Multimodal Reward Models","created":"2025-03-05","cited_by_count":2,"area":"alignment"},{"id":"2503.12301","title":"One Goal, Many Challenges: Robust Preference Optimization Amid Content-Aware and Multi-Source Noise","created":"2025-03-16","cited_by_count":2,"area":"alignment"},{"id":"2507.17107","title":"Reinforcement Learning Fine-Tunes a Sparse Subnetwork in Large Language Models","created":"2025-07-23","cited_by_count":2,"area":"alignment"},{"id":"2506.05260","title":"LeanPO: Lean Preference Optimization for Likelihood Alignment in Video-LLMs","created":"2025-06-05","cited_by_count":1,"area":"alignment"},{"id":"2510.10509","title":"MARS-Sep: Multimodal-Aligned Reinforced Sound Separation","created":"2025-10-12","cited_by_count":1,"area":"alignment"},{"id":"2602.01068","title":"From Utterance to Vividity: Training Expressive Subtitle Translation LLM via Adaptive Local Preference Optimization","created":"2026-02-01","cited_by_count":1,"area":"alignment"},{"id":"2505.06284","title":"DMRL: Data- and Model-aware Reward Learning for Data Extraction","created":"2025-05-07","cited_by_count":0,"area":"alignment"},{"id":"2508.14391","title":"Hallucination-Resistant Relation Extraction via Dependency-Aware Sentence Simplification and Two-tiered Hierarchical Refinement","created":"2025-08-20","cited_by_count":0,"area":"alignment"},{"id":"2510.00647","title":"MCM-DPO: Multifaceted Cross-Modal Direct Preference Optimization for Alt-text Generation","created":"2025-10-01","cited_by_count":0,"area":"alignment"},{"id":"2602.02063","title":"See2Refine: Vision-Language Feedback Improves LLM-Based eHMI Action Designers","created":"2026-02-02","cited_by_count":0,"area":"alignment"},{"id":"2602.23438","title":"DesignSense: A Human Preference Dataset and Reward Modeling Framework for Graphic Layout Generation","created":"2026-02-26","cited_by_count":0,"area":"alignment"},{"id":"2604.05445","title":"Learning What Matters: Dynamic Dimension Selection and Aggregation for Interpretable Vision-Language Reward Modeling","created":"2026-04-07","cited_by_count":0,"area":"alignment"},{"id":"2604.10966","title":"You Only Judge Once: Multi-response Reward Modeling in a Single Forward Pass","created":"2026-04-13","cited_by_count":0,"area":"alignment"},{"id":"2606.01561","title":"S-SPPO: Semantic-Calibrated Self-Play Preference Optimization","created":"2026-06-01","cited_by_count":0,"area":"alignment"},{"id":"2608.19598","title":"PEA-DPO: Perception-Enhanced Alignment Direct Preference Optimization for MLLMs Alignment","created":"2026-08-20","cited_by_count":0,"area":"alignment"},{"id":"2610.12707","title":"Unsupervised Multimodal Reward Modeling","created":"2026-10-08","cited_by_count":0,"area":"alignment"}],"next_cursor":null}